1d:T7c6,# Easy simulation of PK models Easy simulation of basic PK models See http://simulx.webpopix.org/mlxr/pkmodel/ for more details. ```r pkmodel(time, treatment, parameter) ``` ## Arguments - `time`: a vector - `treatment`: a list with fields * `time` : a vector of input times, * `amount` : a scalar or a vector of amounts, * `rate` : a scalar or a vector of infusion rates (default=`Inf`), * `tinf` : a scalar or a vector of infusion times (default=0), - `parameter`: vector of parameters with their names and values ## Examples ```r ## Not run: adm <- list(time=c(2,14,20), amount=40) p <- c(V=8, Cl=0.5,k12=0.3, k21=0.2) t <- seq(0, 30, by=0.1) res <- pkmodel(time = t, treatment = adm, parameter = p) print(ggplot(data=res, aes(x=time, y=cc)) + geom_line(size=1) + xlab("time (h)") + ylab("concentration (mg/L)")) adm <- list(time = c(1,23,37,45), amount = c(1,0.5,2,0.3)) p <- c(Mtt=5, Ktr=1, ka=0.5, V=10, Vm=1, Km=0.6, p=0.5) t <- seq(0, 80, by=0.1) res <- pkmodel(t,adm,p) print(ggplot(data=res, aes(x=time, y=cc)) + geom_line(size=1) + xlab("time (h)") + ylab("concentration (mg/L)")) adm <- list( time = 2, amount = 40) p <- inlineDataFrame(" id ka V Cl 1 0.5 4 1 2 1 6 1 3 1.5 6 1.5 ") t <- seq(0, 30, by=0.1) res <- pkmodel(t,adm,p) print(ggplot(data=res, aes(x=time, y=cc, colour=id)) + geom_line(size=1) + xlab("time (h)") + ylab("concentration (mg/L)")) adm <- list(time=seq(2, 100, by=24), amount=40, rate=5) p <- c(V=8, Cl=0.5, k12=0.3, k21=0.2, ke0=0.2) t <- seq(0, 50, by=0.1) res <- pkmodel(t,adm,p) if( require("reshape2") ){ r <- melt(res, id='time', variable.name='c') print(ggplot(r, aes(time,value)) + geom_line(aes(colour = c),size=1) + ylab('concentration') + guides(colour=guide_legend(title=NULL)) + theme(legend.position=c(.9, .8))) } ## End(Not run) ```

pkmodel function